The IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021) Doctoral Consortium aims to provide a forum for doctoral students to discuss their research and career objectives with experienced researchers of international repute. One of the unique benefits of the consortium is the networking environment to establish new contacts and collaborations with other researchers. It will also serve to spread awareness amongst the students about career options in both academia and industry.

The FG 2021 Doctoral Consortium will be a virtual event, starting with an informal introduction by senior researchers followed by doctoral students. Following this, student participants will present their research and receive feedback from the invited committee. The students will also be paired with a mentor from the committee on the conference platform and can interact with their mentor during the conference directly on specific topics of interest.

Doctoral students working on research problems related to the FG community are invited to apply for the Doctoral Consortium. Successful applicants are expected to actively participate in the consortium and the conference. A best doctoral consortium application award will be given to the top applicant.

 

IMPORTANT DATES

Submission Deadline: November 07, 2021 November 20, 2021
Notification of Acceptance: November 14, 2021 November 25, 2021
Doctoral Consortium Date: TBA, 2021

 

ACCEPTED APPLICATIONS

Title	Author
Child Face Age Progression and Regression to find the Missing Children	Praveen Kumar Chandaliya
Automatic Eye Gaze Estimation with Limited Supervision	Shreya Ghosh
Investigating Deep Learning Spatio-Temporal Modelling and Spatial Attention Systems for Micro-Expression Recognition	Mengjiong Bai
Interpretation of Combined and Complex Charts for Potent Summaries	Prerna Mishra
Fairness and Bias in Face and Ocular Based Machine Learning Systems	Sreeraj Ramachandran
Harnessing unlabeled data for biometric face-based soft biometrics	Aakash Varma Nadimpalli
A Picture is Worth a Thousand Words: Realistic Facial Image Generation from Text Description	Yutong Zhou
Fake Video Content Detection Using Physiological Parameters	Lokendra Birla

 

ELIGIBILITY

We encourage submissions from doctoral students working on their dissertations with partially published results. We encourage diversity and equality, both in terms of research topics as well as participating institutions and individuals. We do not expect more than two students to be invited from each institution to represent a diverse sample. Women are especially encouraged to apply. It is not necessary to have a paper appearing in FG 2021 in order to apply to participate.
 

SUBMISSION

To apply for the Doctoral Consortium, please submit:

• A CV (max 1 page);
• n extended abstract (max 4 pages) following the FG 2021 paper format. It should describe the research vision of the applicant, a brief summary of the work till date, a working plan, and a discussion of future plans and challenges. The work should still be in progress;
• A supporting letter from the thesis advisor that endorses the student’s application to this Doctoral Consortium and briefly describes the progress or status of the student’s thesis work.

NOTE: All materials should be combined into a single PDF file and submitted through the FG 2021 submission system.

 

REVIEW AND SELECTION PROCESS

All submissions will be peer-reviewed by the Doctoral Consortium Technical Program Committee (TPC) members. Paper topics should be related to the conference topics.
Submissions will be evaluated on:

• Quality of the submission;
• Expected benefits for the student’s research;
• Student’s contribution to the diversity of topics, backgrounds, methodology, etc.

SUBMISSION PORTAL: https://cmt3.research.microsoft.com/FGDC2021

 

CONTACT

For further questions, contact the Doctoral Consortium Chairs
Abhinav Dhalll, Monash University, Australia
Sunpreet Singh Arora, Visa Research, USA

 

PROGRAM COMMITTEE/MENTORS

Shaun Canavan, University of South Florida
Oya Celiktutan, Kings College London
Antitza Dantcheva, INRIA
Tejas Dhamecha, IBM Research
Roland Goecke, University of Canberra
Éric Granger, École de technologie supérieure
Zakia Hammal, Carnegie Mellon University
Laszlo A. Jeni, Carnegie Mellon University
Xiaoming Liu, Michigan State University
Subrahmanyam Murala, Indian Institute of Technology Ropar
Gian Luca Marcialis, University of Cagliari
Ajita Rattani, Wichita State University
Karan Sikka, SRI International
Massimo Tistarelli, University of Sassari
Yan Tong, University of South Carolina